1. Field of the Invention
The present invention applies to the field of finding timing of received signals in radio communications systems and, in particular, to finding timing using two-passes through a periodic training sequence.
2. Description of the Prior Art
Mobile radio communications systems such as cellular voice and data radio systems typically have several base stations in different locations available for use by mobile or fixed user terminals, such as cellular telephones or wireless web devices. Each base station typically is assigned a set of frequencies or channels to use for communications with the user terminals. The channels are different from those of neighboring base stations in order to avoid interference between neighboring base stations. As a result, the user terminals can easily distinguish the transmissions received from one base station from the signals received from another. In addition, each base station can act independently in allocating and using the channel resources assigned to it.
Such radio communications systems typically include a broadcast channel (BCH). The BCH is broadcast to all user terminals whether they are registered on the network or not and informs the user terminals about the network. In order to access the network, a user terminal normally tunes to and listens to the BCH before accessing the network. It will then use the information in the BCH to request access to the network. Such a request typically results in an exchange of information about the network using separate control and access channels and ends in the user terminal receiving an assignment to a particular base station.
While frequency and timing offset or delay can sometimes be determined by a user terminal based on the BCH, the initial request for access is typically transmitted by the user terminal without any knowledge of its distance to the base station, its timing delay or the direction to the base station. In a spatial diversity multiple access system, the base station can enhance the capacity of the system by determining the position and range to the user terminal as well as any other spatial parameters. The timing uncertainty of the arrival time of such request messages are proportional to the round trip delay encountered by messages traveling between the base station and the mobile terminal. For systems with a high coverage area per base station, this range and therefore the delay uncertainty may be very large. For example, a range of fifteen km results in a roundtrip delay time of around 100 microseconds.
In order to accurately resolve the access request and determine spatial parameters the timing or delay, frequency offset and spatial signature of the user terminal""s message are all desired. Typically, it is preferred to accurately determine the timing or delay and frequency offset based on analyzing a long training sequence across a potentially long delay spread. This can create great demands on the processing resources of a base station and increase the amount of time required to generate a reply to the access request.
A method and apparatus are provided that allows a coarse timing approximation to be determined from analyzing only a portion of a received burst. The coarse timing can be refined by focusing on the coarse timing approximation. According to one aspect of the present invention, the invention includes receiving a burst having a known repeating core training sequence, selecting an analysis window to be substantially the same size as a multiple of a single repetition of the core training sequence, and over sampling the received burst for the portion overlapping the analysis window. The invention further includes calculating a cross correlation vector for a portion of the samples with respect to a selected part of the training sequence, each cross correlation vector corresponding to a relative timing hypothesis and each cross correlation vector combining samples that occur at intervals within the analysis window, the intervals corresponding to the period of the repeating core training sequence, calculating a least squares fit for each hypothesis using the calculated cross correlation vectors; and selecting the combination of samples corresponding to the minimal least squares fit as the relative timing of the selected part of the repeating core training sequence.